• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.120-128
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• 2010

A hypernetwork is a generalized hypo-graph and a probabilistic graphical model based on evolutionary learning. Hypernetwork models have been applied to various domains including pattern recognition and bioinformatics. Nevertheless, conventional hypernetwork models have the limitation that they can manage data with categorical or discrete attibutes only since the learning method of hypernetworks is based on equality comparison of hyperedges with learned data. Therefore, real-valued data need to be discretized by preprocessing before learning with hypernetworks. However, discretization causes inevitable information loss and possible decrease of accuracy in pattern classification. To overcome this weakness, we propose a novel feature-wise L1-distance based method for real-valued attributes in learning hypernetwork models in this study. We show that the proposed model improves the classification accuracy compared with conventional hypernetworks and it shows competitive performance over other machine learning methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.775-784
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• 2019

Malware infringement attacks are continuously increasing in various environments such as mobile, IOT, windows and mac due to the emergence of new and variant malware, and signature-based countermeasures have limitations in detection of malware. In addition, analytical performance is deteriorating due to obfuscation, packing, and anti-VM technique. In this paper, we propose a system that can detect malware based on machine learning by using similarity hashing-based pattern detection technique and static analysis after file classification according to packing. This enables more efficient detection because it utilizes both pattern-based detection, which is well-known malware detection, and machine learning-based detection technology, which is advantageous for detecting new and variant malware. The results of this study were obtained by detecting accuracy of 95.79% or more for benign sample files and malware sample files provided by the AI-based malware detection track of the Information Security R&D Data Challenge 2018 competition. In the future, it is expected that it will be possible to build a system that improves detection performance by applying a feature vector and a detection method to the characteristics of a packed file.

• Journal of Satellite, Information and Communications
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• v.9 no.2
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• pp.74-79
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• 2014

Conventional ScanSAR mode has been adopted in Envisat or Radarsat and played an important role to acquire wide swath SAR images for environmental surveillance. However, it suffers from the undesirable scalloping effect caused by non-homogeneity of antenna pattern while the image resolution is sacrificed. In recent years, TOPS mode has been suggested and put into use to overcome the disadvantages of the conventional scanning mode. Although TOPS mode is able to produce wide-swath SAR image in a short time interval, it demands highly complicated system design knowledge. In this paper, we present the operation principle of TOPS mode and a full SAR simulation is performed to generate TOPS SAR raw data. Azimuth antenna pattern is modified during TOPS mode operation and it is shown that the undesired scalloping effect is suppressed in the generated SAR image.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.123-130
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• 2009

Motion estimation (ME) plays an important role in digital video compression. But it limits the performance of image quality and encoding speed and is computational demanding part of the encoder. To reduce computational time and maintain the image quality, integer pel and fractional pel ME methods are proposed in this paper. The proposed method for integer pel ME uses a hierarchical search strategy. This strategy method consists of symmetrical cross-X pattern, multi square grid pattern, diamond patterns. These search patterns places search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum and to reduce the computational time. The proposed method for fractional pel uses full search pattern, center biased fractional pel search pattern and the proposed search pattern. According to block sizes, the proposed method for fractional pel decides the search pattern adaptively. Experiment results show that the speedup improvement of the proposed method over Unsymmetrical cross Multi Hexagon grid Search (UMHexagonS) and Full Search (FS) can be up to around $1.2{\sim}5.2$ times faster. Compared to image quality of FS, the proposed method shows an average PSNR drop of 0.01 dB while showing an average PSNR gain of 0.02 dB in comparison to that of UMHexagonS.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.817-827
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• 2014

In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. The degradation results in noise and blurring which badly affect identification and extraction of useful information in image data. This study proposes a maximum a posteriori (MAP) estimation using Point-Jacobian iteration to restore a degraded image. The proposed method assumes a Gaussian additive noise and Markov random field of spatial continuity. The proposed method employs a neighbor window of spoke type which is composed of 8 line windows at the 8 directions, and a boundary adjacency measure of Mahalanobis square distance between center and neighbor pixels. For the evaluation of the proposed method, a pixel-wise classification was used for simulation data using various patterns similar to the structure exhibited in high resolution imagery and an unsupervised segmentation for the remotely-sensed image data of 1 mspatial resolution observed over the north area of Anyang in Korean peninsula. The experimental results imply that it can improve analytical accuracy in the application of remote sensing high resolution imagery.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.293-295
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• 2012

가상화 기술은 물리적 컴퓨팅 자원을 사용자에게 논리적으로 제공하여 시스템의 효율성을 높이고 유연성을 향상시키기 위한 기술로 서버 통합이나 아마존 EC2와 같은 클라우드 컴퓨팅 환경에서 사용되고 있다. 이러한 가상화 환경에서는 다수의 가상머신들의 동시적인 I/O 수행으로 인해 저장장치에 병목현상이 발생된다. 또한 각 가상머신들의 중복된 데이터들을 저장하기 위해 불필요한 쓰기 비용이 발생하여 시스템의 성능 저하가 발생하게 된다. 본 논문에서는 이러한 가상화 환경에서의 I/O비용을 감소시키기 위해 SSD를 캐시로 사용하는 중복 제거 기법을 제안한다. 제안된 기법은 중복된 데이터를 제거하여 불필요한 디스크에 대한 I/O 수행을 감소시키며, 중복 발생 패턴의 특성을 고려하여 SSD의 빠른 쓰기 성능을 효과적으로 사용할 수 있는 캐시 구조 모델을 통해 가상화 환경에서 I/O 성능을 향상 시킬 수 있음을 보인다.

• Aerospace Engineering and Technology
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• v.5 no.2
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• pp.108-113
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• 2006

This paper includes the test results of KOMPSAT-2 payload downlink system which were measured for the purpose of performance verification. The antenna beam patterns which indicates the status of the interface & antenna itself, were measured as well as the antenna VSWR. The checkout of the transponder & its spectrum was followed and this made sure that there was no spurious output distinguished. Finally a test for BER verification was conducted between satellite and receiving system for their compatibility through the antenna-to-antenna connection using an antenna hat. Verification tests for an RF system should be performed after relocation, integration and test for environments in order to make sure that no degradation happens.

• The Journal of the Acoustical Society of Korea
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• v.34 no.1
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• pp.75-81
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• 2015

In active sonar system, clutters degrade performance of target detection/tracking and overwhelm sonar operators in ASW (Antisubmarine Warfare). Conventional clutter reduction algorithms using consistency of local peaks are studied in multi-ping data and tracking filter research for active sonar was conducted. However these algorithms cannot classify target and clutters in single ping data. This paper suggests a single ping clutter reduction approach to reduce clutters in mid-frequency active sonar system using echo shape features. The algorithm performance test is conducted using real sea-trial data in heavy clutter density environment. It is confirmed that the number of clutters was reduced by about 80 % over the conventional algorithm while retaining the detection of target.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.43-48
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• 2013

Adaboost is widely used for Haar-like feature boosting algorithm in Face Detection. It shows very effective performance on single distribution model. But when detecting front and side face images at same time, Adaboost shows it's limitation on multiple distribution data because it uses linear combination of basic classifier. This paper suggest the HDCT, modified decision tree algorithm for Haar-like features. We still tested the performance of HDCT compared with Adaboost on multiple distributed image recognition.

• The KIPS Transactions:PartC
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• v.16C no.4
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• pp.449-460
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• 2009

The signature hashing algorithm[9] provides the fast pattern matching speed for network IPS(Intrusion Prevention System) using the hash table. It selects 2 bytes from all signature rules and links to the hash table by the hash value. It has an advantage of performance improvement because it reduces the number of inspecting rules in the pattern matching. However it has a disadvantage of performance drop if the number of rules with the same hash value increases when the number of rules are large and the corelation among rules is strong. In this paper, we propose a method to make all rules distributed evenly to the hash table independent of the number of rules and corelation among rules for overcoming the disadvantage of the signature hashing algorithm. In the proposed method, it checks whether or not there is an already assigned rule linked to the same hash value before a new rule is linked to a hash value in the hash table. If there is no assigned rule, the new rule is linked to the hash value. Otherwise, the proposed method recalculate a hash value to put it in other position. We implemented the proposed method in a PC with a Linux module and performed experiments using Iperf as a network performance measurement tool. The signature hashing method shows performance drop if the number of rules with the same hash value increases when the number of rules are large and the corelation among rules is strong, but the proposed method shows no performance drop independent of the number of rules and corelation among rules.